Machine learning for adverse event prediction in outpatient parenteral antimicrobial therapy: a scoping review
Douglas W Challener,
Madiha Fida,
Peter Martin
et al.
Abstract:Objective
This study aimed to conduct a scoping review of machine learning (ML) techniques in outpatient parenteral antimicrobial therapy (OPAT) for predicting adverse outcomes and to evaluate their validation, implementation and potential barriers to adoption.
Materials and methods
This scoping review included studies applying ML algorithms to adult OPAT patients, covering techniques from logistic regression to neural networ… Show more
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